Statistical Analysis of the DN/dS Ratio in DNA Sequences: Structure, Function and Evolution.

DNA 序列中 DN/dS 比率的统计分析：结构、功能和进化。

• 批准号: 0089487
• 负责人: Rasmus Nielsen
• 金额: $ 23.6万
• 依托单位: Cornell Univ - State: AWDS MADE PRIOR MAY 2010
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-04-15 至 2004-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0089487&HistoricalAwards=false
• 关键词: Statistical; Analysis; DN; dS; Ratio

By identifying natural selection at the level of DNA sequences, it possible to address questions regarding molecular evolution and to identify genomic regions or sites in the DNA sequence of special functional importance. In this project new statistical methods for identifying and interpreting patterns of selection will be developed. A Bayesian method based on Markov chain Monte Carlo (MCMC) will be developed that will provide a more powerful and versatile tool for identifying selection at the level of the DNA sequence. Methods for estimating the age of a mutation, for estimating the distribution of selection coefficients and for detecting correlated evolution in DNA sequences will also be developedThe new methods will be applied to several data sets, particularly data sets of viral sequences such as HIV-1 sequences. One of the questions that will be addressed is how often compensatory mutations occur in the evolution of drug resistance in the HIV-1 virus. The new methods will be applicable in many genomic studies, particularly for identifying regions or sites of functional importance.

通过在DNA序列水平上识别自然选择，就有可能解决有关分子进化的问题，并在DNA序列中识别具有特殊功能重要性的基因组区域或位点。在这个项目中，将发展用于识别和解释选择模式的新的统计方法。基于马尔可夫链蒙特卡罗（MCMC）的贝叶斯方法将被开发，这将为识别DNA序列水平的选择提供更强大和通用的工具。还将开发用于估计突变年龄、估计选择系数分布和检测DNA序列中相关进化的方法。新方法将应用于几个数据集，特别是病毒序列（如HIV-1序列）的数据集。要解决的问题之一是，在HIV-1病毒耐药性的进化过程中，补偿性突变发生的频率。新方法将适用于许多基因组研究，特别是用于识别具有重要功能的区域或位点。